research A Novel Fusion Technique for Early Detection of Alopecia Areata Using ResNet-50 and CRSHOG
AlopeciaDet accurately detects Alopecia Areata early using advanced image analysis.
Search
for
Sort by
Research
30 / 1000+ resultsresearch Deep Learning-Powered Hair Disease Diagnosis: A ResNet50 Approach for Scalable and Accurate Classification
The model accurately diagnoses hair diseases with 95% accuracy using deep learning.
research Harnessing Deep Learning for Scalp and Hair Disease Classification: A Comparative Study of Convolutional Neural Networks Architectures
VGG16 and VGG19 are the most accurate for classifying scalp and hair diseases.
research A Hybrid Deep Learning System for Automatic Detection of Scalp Diseases and Hair Fall Stage Classification
The system effectively detects scalp diseases and classifies hair fall stages with high precision.
research HairLossMultinet: A Multi Scale Feature Fusion Method Using Deep Learning Approach
HairLossMultinet accurately classifies hair damage with 98% accuracy but needs a more diverse dataset for broader use.
research Methods of Transfer Learning for Multiclass Hair Disease Categorization
Transfer learning with three neural network architectures accurately classifies hair diseases.
research A Comprehensive Survey on Vitiligo Detection Using Deep Learning
Better datasets and methods are needed for reliable vitiligo detection using deep learning.
research Big Self-Supervised Models Advance Medical Image Classification
Self-supervised learning improves medical image classification accuracy.
research Deep Clustering via Center-Oriented Margin Free-Triplet Loss for Skin Lesion Detection in Highly Imbalanced Datasets
The new method improves skin cancer detection in imbalanced datasets.
research AB-MTEDeep Classifier Trained with AAGAN for the Identification and Classification of Alopecia Areata
The AI model accurately classifies Alopecia Areata with 96.94% accuracy.
research Deep Learning-Based Dermatological Condition Detection: A Systematic Review With Recent Methods, Datasets, Challenges, and Future Directions
Deep learning helps detect skin conditions and is advancing dermatology diagnosis and treatment.
research 448 Challenges of securing insurance approval for oral tofacitinib treatment of alopecia areata: A multi-institutional retrospective review
Getting insurance to cover the hair loss treatment tofacitinib is hard because it's not officially approved for that use.
research Generative adversarial networks for anonymous acneic face dataset generation
The method creates realistic, anonymous acne face images for research, achieving 97.6% accuracy in classification.
research Detection of Meibomian Gland Dysfunction by in vivo Confocal Microscopy Based on Deep Convolutional Neural Network
The model can effectively help diagnose meibomian gland dysfunction automatically.
research Optimizing skin disease diagnosis: harnessing online community data with contrastive learning and clustering techniques
Researchers improved a skin disease diagnosis model using online images, achieving up to 49.64% accuracy.
research BAYONET trial: staged combination with encorafenib, binimetinib, plus cetuximab following encorafenib plus cetuximab for BRAF V600E-mutant metastatic colorectal cancer
The combination treatment showed a higher response rate but no significant survival benefits.
research 44047 Long Term Real-World Treat-to-Target Skin Clearance and Maintenance of Response with Risankizumab in Patients with Moderate to Severe Psoriasis From the CorEvitas Psoriasis Registry
Risankizumab effectively treats and maintains skin clearance in moderate-to-severe psoriasis.
research PULMONARY DELIVERY OF RESVERATROL-LOADED NANOCOMPOSITE MICROPARTICLES TO TREAT LUNG CANCER
Resveratrol-loaded nanoparticles show promise for lung cancer treatment.
research Skin image analysis for detection and quantitative assessment of dermatitis, vitiligo and alopecia areata lesions: a systematic literature review
Computer vision techniques can help detect and assess skin conditions like vitiligo, alopecia areata, and dermatitis.
research Integration of Colorimetric Sensing Dyes and Multi‐Substrate Arrays for Food Quality and Safety Monitoring: Design, Optimization, and Analysis
Combining advanced sensors with portable devices could enhance on-site food safety monitoring.
research Leveraging deep neural networks to uncover unprecedented levels of precision in the diagnosis of hair and scalp disorders
A new AI model diagnoses hair and scalp disorders with 92% accuracy, better than previous models.
research Automating Hair Loss Labels for Universally Scoring Alopecia From Images
The AI system HairComb accurately scores hair loss severity, matching dermatologist assessments.
research Artificial intelligence in dermatology: а scoping review
AI in dermatology shows high accuracy in diagnosing skin diseases but needs more research for improvement.
research 778 Designing and utilizing a c-Rel specific bioassay in drug repurposing screen for HNSCC
A new test helps find drugs to treat head and neck cancer by targeting c-Rel.
research Efficacy and safety evaluations of topical proretinal nanoparticles
Proretinal nanoparticles are a safe and effective way to deliver retinal to the skin.
research The Rotterdam Study: 2010 objectives and design update
The Rotterdam Study aims to understand various diseases in older adults.
research 43364 Long Term Real-World Patient-Reported Outcomes with Risankizumab in Patients with Moderate to Severe Psoriasis From the CorEvitas Psoriasis Registry
research Long-Term Efficacy and Complete Scalp Hair Regrowth in Patients With Alopecia Areata Receiving Ritlecitinib 50 mg QD Up to 3 Years in the ALLEGRO Clinical Trial Program
Ritlecitinib 50 mg effectively promotes and sustains hair regrowth in alopecia areata patients.
research Translating Resveratrol Research: A Systematic Review on Patents and Clinical Trials (2000–2025)
Resveratrol shows health benefits but faces challenges in effectiveness and regulation.
research Hair Follicle Classification and Hair Loss Severity Estimation Using Mask R-CNN
An intelligent system can classify hair follicles and measure hair loss severity with reasonable accuracy.